Using genetic algorithms to solve the multi-product JIT sequencing problem with set-ups

Abstract

This paper presents a methodology to solve the Just-in-Time (JIT) sequencing problem for multiple product scenarios when set-ups between products are required. Problems of this type are combinatorial, and complete enumeration of all possible solutions is computationally prohibitive. Therefore, Genetic Algorithms are often employed to find desirable, although not necessarily optimal, solutions. This research, through experimentation, shows that Genetic Algorithms provide formidable solutions to the multi-product JIT sequencing problem with set-ups. The results also compare favourably to those found using the search techniques of Tabu Search and Simulated Annealing.